Estimating jaguar densities with camera traps: Problems with current designs and recommendations for future studies

Camera traps have become the main method for estimating jaguar (Panthera onca) densities. Over 74 studies have been carried out throughout the species range following standard design recommendations. We reviewed the study designs used by these studies and the results obtained. Using simulated data we evaluated the performance of different statistical methods for estimating density from camera trap data including the closed-population capture–recapture models Mo and Mh with a buffer of ½ and the full mean maximum distance moved (MMDM) and spatially explicit capture–recapture (SECR) models under different study designs and scenarios. We found that for the studies reviewed density estimates were negatively correlated with camera polygon size and MMDM estimates were positively correlated. The simulations showed that for camera polygons that were smaller than approximately one home range density estimates for all methods had a positive bias. For large polygons the Mh MMDM and SECR model produced the most accurate results and elongated polygons can improve estimates with the SECR model.

When encounter rates and home range sizes varied by sex, estimates had a negative bias for models that did not include sex as a covariate. Based on the simulations we concluded that the majority of jaguar camera trap studies did not meet the requirements necessary to produce unbiased density estimates and likely overestimated true densities. We make clear recommendations for future study designs with respect to camera layout, number of cameras, study length, and camera placement. Our findings directly apply to camera trap studies of other large carnivores.